hackathon-kin

Hackathon Kin: Customers churn (Finance and Risk).

Classification project based on Supervised Machine Learning using Logistic Regression, Random Forest, K-Neighbours, SVC, Decision Tree, Gradient Boosting, XGB, LGBM, Cat Boost, Ada Boost and ANN.\

Requirements

Python 3.10+

Git

First, clone repository:

git clone https://github.com/jpcadena/hackathon-kin.git

Change directory to root project with:

  cd hackathon-kin

Create your git branch with the following:

git checkout -b <new_branch>

For <new_branch> use some convention as following:

yourgithubusername

Or if some work in progress (WIP) or bug shows up, you can use:

yourgithubusername_feature

Switch to your branch:

git checkout <new_branch>

Before you start working on some section, retrieve the latest changes with:

git pull

Add your new files and changes:

git add .

Make your commit with a reference message about the fix/changes.

git commit -m "Commit message"

First push for remote branch:

git push --set-upstream origin <new_branch>

Latter pushes:

git push origin

Environment

Create a virtual environment 'sample_venv' with:

python3 -m venv sample_venv

Activate environment in Windows with:

.\sample_venv\Scripts\activate

Or with Unix or Mac:

source sample_venv/bin/activate

Installation of libraries and dependencies

pip install -r requirements.txt

Execution

python main.py

Documentation

Use docstrings with reStructuredText format by adding triple double quotes """ after function definition.
Add a brief function description, also for the parameters including the return value and its corresponding data type.

Additional information

If you want to give more style and a better format to this README.md file, check documentation at GitHub Docs.
Please use linting to check your code quality following PEP 8. Check documentation for Visual Studio Code or for Jetbrains Pycharm.
Recommended plugin for autocompletion: Tabnine